CNNS FOR ENHANCED BIOMEDICAL SIGNAL CLASSIFICATION AND INTERPRETATION

Abstract

The evolution of signal analysis from manual recording to automated systems has been pivotal in the field of medical research. The inception of the electrocardiograph in 1902 marked a milestone, providing crucial insights into cardiac structure and function (AlGhatrif and Lindsay, 2012). Augustus Waller further advanced this frontier in 1937 with the introduction of the first human electrocardiogram, employing a capillary electrometer and chest-mounted electrodes (AlGhatrif and Lindsay, 2012). Subsequently, in 1938, Denny-Brown made significant strides by delineating fasciculation potentials and separating them from fibrillations (Kazamel and Warren, 2017). Lambert and Eaton, in 1957, elucidated the electrophysiologic framework of myasthenic syndromes linked to lung cancer. Regarding EEG signals, the visual examination persisted from 1929 until the late 1960s, when the advent of digital tools revolutionized the field ("History: From EEG to Quantitative EEG (QEEG)," 2017).